Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2008 IEEE International Conference on Systems, Man and Cybernetics |
| Seiten | 757-762 |
| Seitenumfang | 6 |
| Publikationsstatus | Veröffentlicht - 2008 |
| Veranstaltung | 2008 IEEE International Conference on Systems, Man and Cybernetics, SMC 2008 - Singapore, Singapur Dauer: 12 Okt. 2008 → 15 Okt. 2008 |
Publikationsreihe
| Name | Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics |
|---|---|
| ISSN (Print) | 1062-922X |
Abstract
We compare two approaches for misbehavior detection in sensor wireless networks based on Artificial Immune Systems (AIS) and Neural Networks (NN). We conclude that AIS and NN based misbehavior detection offers a decent detection performance at a very low computational cost. However both approaches are different regarding the length of the preprocessing phase, memory requirements, speed of computation and the rate of false positives. Both approaches are suitable for misbehavior detection in sensor networks, the decision which approach to choose for a specific sensor network depends on the details of the scenario.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Elektrotechnik und Elektronik
- Ingenieurwesen (insg.)
- Steuerungs- und Systemtechnik
- Informatik (insg.)
- Mensch-Maschine-Interaktion
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- BibTex
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2008 IEEE International Conference on Systems, Man and Cybernetics. 2008. S. 757-762 (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Comparing performance of misbehavior detection based on neural networks and AIS
AU - Becker, Matthias
AU - Drozda, Martin
AU - Jaschke, Sebastian
AU - Schaust, Sven
PY - 2008
Y1 - 2008
N2 - We compare two approaches for misbehavior detection in sensor wireless networks based on Artificial Immune Systems (AIS) and Neural Networks (NN). We conclude that AIS and NN based misbehavior detection offers a decent detection performance at a very low computational cost. However both approaches are different regarding the length of the preprocessing phase, memory requirements, speed of computation and the rate of false positives. Both approaches are suitable for misbehavior detection in sensor networks, the decision which approach to choose for a specific sensor network depends on the details of the scenario.
AB - We compare two approaches for misbehavior detection in sensor wireless networks based on Artificial Immune Systems (AIS) and Neural Networks (NN). We conclude that AIS and NN based misbehavior detection offers a decent detection performance at a very low computational cost. However both approaches are different regarding the length of the preprocessing phase, memory requirements, speed of computation and the rate of false positives. Both approaches are suitable for misbehavior detection in sensor networks, the decision which approach to choose for a specific sensor network depends on the details of the scenario.
KW - Artificial Immune Systems
KW - Misbehavior detection
KW - Neural Networks
KW - Sensor networks
UR - http://www.scopus.com/inward/record.url?scp=69949168469&partnerID=8YFLogxK
U2 - 10.1109/ICSMC.2008.4811369
DO - 10.1109/ICSMC.2008.4811369
M3 - Conference contribution
AN - SCOPUS:69949168469
SN - 978-1-4244-2383-5
T3 - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
SP - 757
EP - 762
BT - 2008 IEEE International Conference on Systems, Man and Cybernetics
T2 - 2008 IEEE International Conference on Systems, Man and Cybernetics, SMC 2008
Y2 - 12 October 2008 through 15 October 2008
ER -